Analytical sensor systems that can monitor interactions between molecules, such as biomolecules, in real time are gaining increasing interest. These systems are often based on optical biosensors and usually referred to as interaction analysis sensors or biospecific interaction analysis sensors. A representative such biosensor system is the BIACORE® instrumentation sold by GE Healthcare, which uses surface plasmon resonance (SPR) for detecting interactions between molecules in a sample and molecular structures immobilized on a sensing surface. As sample is passed over the sensor surface, the progress of binding directly reflects the rate at which the interaction occurs. Injection of sample is followed by a buffer flow during which the detector response reflects the rate of dissociation of the complex on the surface. A typical output from the BIACORE® system is a graph or curve describing the progress of the molecular interaction with time, including an association phase part and a dissociation phase part. This binding curve, which is usually displayed on a computer screen, is often referred to as a binding curve or “sensorgram”.
With the BIACORE® system (and analogous sensor systems) it is thus possible to determine in real time without the use of labeling, and often without purification of the substances involved, not only the presence and concentration of a particular molecule (analyte) in a sample, but also additional interaction parameters, including kinetic rate constants for binding (association) and dissociation in the molecular interaction as well as the affinity for the surface interaction. The association rate constant (ka) and the dissociation rate constant (kd) can be obtained by fitting the resulting kinetic data for a number of different sample analyte concentrations to mathematical descriptions of interaction models in the form of differential equations. The affinity (expressed as the affinity constant KA or the dissociation constant KD) can be calculated from the association and dissociation rate constants.
In order to derive the above interaction parameters from registered binding curves there has been developed a range of different assays and models involving more or less complex calculations which have proven to give very reliable results for many types of interactions. However, many of these calculations are based on a specific interaction model and thus are limited to interactions of a specific type that fall under this model and there are a range of interactions that are not easily categorized according to a specific model. Therefore, it is not always possible to provide reliable interaction parameters for evaluation of some analyte ligand interactions. FIG. 3 disclose two schematic examples of binding curves where the model based evaluation (dashed line) was not able to provide reliable results.
One alternative method to evaluate this type of interactions is to rely on report points at predetermined points in the binding curve. But in analysis based on report points, only information about the interaction at the specific report points is used to characterize the interaction, whereas a majority of the information in the binding curves is discarded.